<scp>CFD</scp> ‐ <scp>DEM</scp> studies of continuous particle drying in a bubbling fluidized bed with large hole perforated plates
Bibliographic record
Abstract
Abstract Continuous particle drying in a countercurrent bubbling fluidized bed is experimentally and numerically studied by heat and mass transfer coupled CFD‐DEM simulations. The aim of this study is to investigate the drying behaviour, flow dynamics, and heat/mass transfer mechanisms in this novel fluidized bed design with large‐hole perforated plates to allow continuous particle discharge. Particle temperatures are monitored by considering the air–particle heat transfer heating and water evaporation cooling simultaneously. The swirling particle flow patterns are observed above the plate. The deviations between the predicted dried particle water content and that of experimental results are within 10.5%. The errors are further reduced with a longer simulation time. At higher drying air velocities, the solids hold‐up increases and the particle mean residence time increases. The spouting flow patterns cause the time‐averaged particle through‐hole discharging flux to linearly increase in the radial direction. The effective drying region is found at about 12 particle diameters above the plate, where the solids volume fraction is the highest. The highest water evaporation rate of 6.5 × 10 −6 g/s is observed around the boundary of the bubbles and within the bubbles at the bed centre. The particle Nusselt and Sherwood numbers analyses show that the convective heat and mass transfer are the major drying mechanisms.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".